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Design et création · SKILL.md

coordinate-swarm

coordinate-swarm

Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck…

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name: coordinate-swarm locale: caveman-ultra source_locale: en source_commit: 82c77053 fence_basis_commit: 82c77053 translator: "Julius Brussee homage — caveman" translation_date: "2026-04-19" description: > Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination. license: MIT allowed-tools: Read metadata: author: Philipp Thoss version: "1.0" domain: swarm complexity: basic language: natural tags: swarm, coordination, stigmergy, emergent-behavior

Coordinate Swarm

Stigmergy + local rules + quorum → coherent collective, no central ctrl.

Use When

  • Distributed sys → no central bottleneck
  • Self-coord teams → no mgr overhead
  • Event-driven arch → shared state, not direct msg
  • Works @3 agents → breaks @30 → scale
  • Bootstrap new swarm domain (forage-resources, build-consensus)
  • Replace fragile central orch → resilient emergent

In

  • Required: Agents desc (workers, services, team)
  • Required: Collective goal / target behavior
  • Optional: Current coord + fail modes
  • Optional: Agent count → pattern choice
  • Optional: Latency tolerance (realtime vs eventual)
  • Optional: Env constraints (shared state, bandwidth)

Do

Step 1: Classify Problem

  1. Map: who agents, what do, where coord breaks
  2. Classify:
    • Foraging → search distributed res (forage-resources)
    • Consensus → agree collective decision (build-consensus)
    • Construction → build shared structure
    • Defense → detect threats (defend-colony)
    • Division of labor → self-organize roles
  3. Fail mode:
    • Single point fail (central ctrl)
    • Comm bottleneck (too many msg)
    • Coherence loss (drift, no feedback)
    • Rigidity (no adapt)

→ Clear class + fail mode → pattern choice.

If err: no single class → composite → decompose. Heterogeneous → layered coord (homogeneous clusters + inter-cluster stigmergy).

Step 2: Design Signals

Indirect comm channels.

  1. Shared env (DB, queue, FS, board)
  2. Signal types:
    • Trail: accumulate on success paths (ant pheromone)
    • Threshold: counter → behavior switch
    • Inhibition: repel from exhausted areas
  3. Props:
    • Decay: fade rate → no stale dominance
    • Reinforce: success strengthens
    • Radius: propagation range
  4. Signal → behavior map:
    • Signal X > T → action A
    • A done → deposit Y
    • No signal → default explore
Signal Design Template:
┌──────────────┬───────────────────┬──────────────┬────────────────────┐
│ Signal Name  │ Deposited When    │ Decay Rate   │ Agent Response     │
├──────────────┼───────────────────┼──────────────┼────────────────────┤
│ success-trail│ Task completed OK │ 50% per hour │ Follow toward      │
│ busy-marker  │ Agent starts task │ On completion│ Avoid / pick other │
│ help-signal  │ Agent stuck >5min │ 25% per hour │ Assist if nearby   │
│ danger-flag  │ Error detected    │ 10% per hour │ Retreat & report   │
└──────────────┴───────────────────┴──────────────┴────────────────────┘

→ Signal table: deposit conds + decay + responses. Simple + composable.

If err: too complex → 2 signals (attract/repel). Add nuance after basic works.

Step 3: Local Rules

Simple rules, local info only.

  1. Perception radius (what sense?)
  2. 3-7 rules, priority order:
    • Rule 1 (safety): danger-flag → flee
    • Rule 2 (response): help-signal + idle → move toward
    • Rule 3 (exploit): success-trail → follow strongest
    • Rule 4 (explore): no signal → random + unexplored bias
    • Rule 5 (deposit): task done → deposit success-trail
  3. Each rule:
    • Local: only what agent perceives
    • Simple: one if-then
    • Stateless (pref): no past mem
  4. Mental test → does collective behavior emerge?

→ Prioritized rules, independent exec → target behavior emerges.

If err: no emergence → feedback loop needed. Add signal for collective state + adjust rule.

Step 4: Quorum Thresholds

Trigger collective changes when enough agree.

  1. Collective decisions:
    • Explore → exploit mode
    • New worksite commit / abandon
    • Normal → emergency
  2. Per decision:
    • Threshold: # / % agents agreeing
    • Window: signal count period
    • Hysteresis: different on/off thresh → no osc
  3. Quorum = signal accumulation:
    • Fav agent → vote-signal
    • Votes > thresh in window → activate
    • Votes < deact thresh → reverse

→ Leaderless decisions. Hysteresis gap → no rapid osc.

If err: oscillation → widen hyst gap (70/30). Never reaches quorum → lower thresh / widen window. Too slow → shrink window (beware premature).

Step 5: Test + Tune

  1. Pilot 5-10 agents
  2. Observe:
    • Converges on behavior?
    • How long?
    • Conditions change mid-task → what?
    • Agents fail / added → what?
  3. Tune params:
    • Decay: fast → no memory; slow → stale dominates
    • Quorum: low → premature; high → paralysis
    • Explore/exploit balance: too explore → inefficient; too exploit → local optima
  4. Stress:
    • Remove 30% agents → recover?
    • Double count → still coord?
    • Conflict signals → resolve / deadlock?

→ Tuned params, self-organizes, recovers, scales.

If err: stress fails → too tightly coupled. Simplify: fewer signals, faster decay, robust default. Swarm w/ zero-signal default > signal-dependent swarm.

Check

  • Problem classified (foraging / consensus / construction / defense / labor)
  • Signal table: deposit + decay + response
  • Rules simple + local + prioritized (3-7)
  • Quorum w/ hysteresis → no osc
  • Small test → emergent behavior matches goal
  • Stress test → graceful degradation

Traps

  • Signal bloat: Too many types → confusion. Start 2 (attract/repel)
  • Fake local: Rule needs global state → not local. Refactor
  • No decay: Fossilized coord state. Half-life per task scale
  • Zero hysteresis: Rapid osc. Deact < act always
  • Homogeneity assumed: Diff caps → role-diff rules (scale-colony)

→

  • forage-resources — res search + explore-exploit
  • build-consensus — distrib agreement deep-dive
  • defend-colony — collective defense on signal framework
  • scale-colony — scaling past initial coord
  • adapt-architecture — morphic arch transform
  • deploy-to-kubernetes — distrib sys deploy
  • plan-capacity — capacity + swarm scaling
  • coordinate-reasoning — AI self-variant; stigmergy → ctx mgmt
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